5 papers
Multi-User Dueling Bandits: A Fair Approach using Nash Social Welfare
Maheed H. Ahmed, Mahsa Ghasemi
Learning from human preference data is becoming a useful tool, from fine-tuning large language models to training reinforcement learning agents. However, in most scenarios, the mod…
Separation Assurance between Heterogeneous Fleets of Small Unmanned Aerial Systems via Multi-Agent Reinforcement Learning
Iman Sharifi, Hyeong Tae Kim, Maheed Hatem Ahmed +2
In the envisioned future dense urban airspace, multiple companies will operate heterogeneous fleets of small unmanned aerial systems (sUASs), where each fleet includes several homo…
A Survey of Security Challenges and Solutions for Advanced Air Mobility and eVTOL Aircraft
Mahyar Ghazanfari, Iman Sharifi, Peng Wei +25
This survey reviews the existing and envisioned security vulnerabilities and defense mechanisms relevant to Advanced Air Mobility (AAM) systems, with a focus on electric vertical t…
A Survey of Security Challenges and Solutions for UAS Traffic Management (UTM) and small Unmanned Aerial Systems (sUAS)
Iman Sharifi, Mahyar Ghazanfari, Abenezer Taye +25
The rapid growth of small Unmanned Aerial Systems (sUAS) for civil and commercial missions has intensified concerns about their resilience to cyber-security threats. Operating with…
Reinforcement Learning from Multi-level and Episodic Human Feedback
Muhammad Qasim Elahi, Somtochukwu Oguchienti, Maheed H. Ahmed +1
Designing an effective reward function has long been a challenge in reinforcement learning, particularly for complex tasks in unstructured environments. To address this, various le…